Insurance organizations around the world are heavily investing in AI. “Recent research by Genpact found that 87% of insurers are planning to invest more than $5 million in AI by 2020 – and more than half want to transform their existing business processes over the next three years because of AI.” (Technative) This race to embrace AI showcases the importance of remaining relevant and competitive in the Fourth Industrial Revolution.
Insurers are using AI for:
- Marketing: To better identify conversion opportunities.
- Underwriting: To allow for more granular differentiation among risk.
- Pricing: To allow for more precise prediction of loss propensity.
- Loss control: To distinguish more precisely among causes of loss in regards to their impact on loss ratios.
- Claims: To implement cost-effective claims “triage.”
With multiple use cases and pain points to address and overcome, how can insurers successfully leverage AI? With automated machine learning. Automated machine learning is a game-changer for insurance companies because it empowers people throughout the organization from actuaries to product managers.
About the Author:
Neal Silbert is DataRobot's General Manager of Insurance. As an insurance industry executive and management consultant, he has served as an analytics thought leader and driver of innovation for the last 25 years. Recently, he was the VP of Predictive Analytics at Zurich North America, focusing on bringing the latest advances in predictive analytics to insurance product development. Neal works closely with our data scientists and customers to define state-of-the-art AI solutions that drive maximum impact across the insurance enterprise.